2 citations · 2 across the 4 of their papers we have counts for
6 papers
From Detection to Decision: Calibration and Deferral for Prompt-Injection Detection
Qianlong Lan, Anuj Kaul, Vinothini Pandurangan +1
Prompt-injection defenses are commonly evaluated as binary detectors, although deployed LLM applications must make operational decisions about whether to allow, block, or escalate…
Beyond F1: Evaluating Coverage and Failure Recovery in AI Model Security Scanners
Qianlong Lan, Vinothini Pandurangan, Anuj Kaul +1
Static scanners are increasingly used to identify executable or otherwise unsafe content in machine- learning artifacts, yet conventional evaluation metrics characterize only cases…
Behavioral Governance for Autonomous AI Agents: The AgentBound Framework
Anuj Kaul, Qianlong Lan, Pranay Gupta
Autonomous AI agents increasingly perform consequential actions on behalf of human principals, including financial transactions, external communications, and enterprise workflows.…
The Cognitive Firewall:Securing Browser Based AI Agents Against Indirect Prompt Injection Via Hybrid Edge Cloud Defense
Qianlong Lan, Anuj Kaul
Deploying large language models (LLMs) as autonomous browser agents exposes a significant attack surface in the form of Indirect Prompt Injection (IPI). Cloud-based defenses can pr…
Silent Egress: When Implicit Prompt Injection Makes LLM Agents Leak Without a Trace
Qianlong Lan, Anuj Kaul, Shaun Jones +1
Agentic large language model systems increasingly automate tasks by retrieving URLs and calling external tools. We show that this workflow gives rise to implicit prompt injection:…
Zero-Trust Runtime Verification for Agentic Payment Protocols: Mitigating Replay and Context-Binding Failures in AP2
Qianlong Lan, Anuj Kaul, Shaun Jones +1
The deployment of autonomous AI agents capable of executing commercial transactions has motivated the adoption of mandate-based payment authorization protocols, including the Unive…